Claudio Agostinelli1, Andrea Gallamini2, Luisa Stracqualursi3, Patrizia Agati3, Claudio Tripodo4, Fabio Fuligni5, Maria Teresa Sista5, Stefano Fanti6, Alberto Biggi7, Umberto Vitolo8, Luigi Rigacci9, Francesco Merli10, Caterina Patti11, Alessandra Romano12, Alessandro Levis13, Livio Trentin14, Caterina Stelitano15, Anna Borra16, Pier Paolo Piccaluga5, Stephen Hamilton-Dutoit17, Peter Kamper17, Jan Maciej Zaucha18, Bogdan Małkowski19, Waldemar Kulikowski20, Joanna Tajer21, Edyta Subocz22, Justyna Rybka23, Christian Steidl24, Alessandro Broccoli25, Lisa Argnani25, Randy D Gascoyne24, Francesco d'Amore17, Pier Luigi Zinzani25, Stefano A Pileri26. 1. Haemopathology Section, Bologna University School of Medicine, Bologna, Italy. Electronic address: claudio.agostinelli@unibo.it. 2. Research, Innovation and Statistics Department, Centre Antoine Lacassagne, Nice, France. 3. Statistics Department, University of Bologna, Bologna, Italy. 4. Tumour Immunology Unit, Human Pathology Section, University of Palermo, Palermo, Italy. 5. Haemopathology Section, Bologna University School of Medicine, Bologna, Italy. 6. Department of Experimental, Diagnostic and Specialty Medicine and Nuclear Medicine Unit, Bologna University School of Medicine, Bologna, Italy. 7. Nuclear Medicine Department, S Croce e Carle Hospital, Cuneo, Italy. 8. Department of Haematology, Città della Salute e della Scienza Hospital, Torino, Italy. 9. Oncology Department, University of Florence, Florence, Italy. 10. Haematology Department, Arcispedale S Maria Nuova, Reggio Emilia, Italy. 11. Haematology Department, Azienda Ospedaliera Cervello, Palermo, Italy. 12. Haematology Department, Catania University School of Medicine, Catania, Italy. 13. Haematology Department, Azienda Ospedaliera S Antonio e Biagio, Alessandria, Italy. 14. Experimental Medicine Department, Padua University School of Medicine, Padua, Italy. 15. Haematology Department, Azienda Ospedaliera Melacrino, Reggio Calabria, Italy. 16. Haematology Department, S Croce e Carle Hospital, Cuneo, Italy. 17. Departments of Haematology and Pathology, Aarhus University Hospital, Aarhus, Denmark. 18. Department of Clinical Oncology, Gdynia Oncology Centre and Department of Propaedeutic Oncology-Medical University of Gdańsk, Gdynia, Poland. 19. Department of Nuclear Medicine, Oncology Centre, Bydgoszcz, Poland. 20. Department of Haematology, Regional Oncology Centre, Olsztyn, Poland. 21. Department of Lymphoproliferative Diseases, Maria Sklodowska-Curie Memorial Institute, Warsaw, Poland. 22. Department of Haematology and Internal Medicine, Military Institute of Medicine, Warsaw, Poland. 23. Department of Haematology, Blood Neoplasms and Bone Marrow Transplantation, Wroclaw Medical University, Wroclaw, Poland. 24. Department of Pathology and Laboratory Medicine, Centre for Lymphoid Cancer, Vancouver, BC, Canada; Department of Lymphoid Cancer Research-BCCRC, British Columbia Cancer Agency, Vancouver, BC, Canada. 25. Haematology Section, Bologna University School of Medicine, Bologna, Italy. 26. Haemopathology Section, Bologna University School of Medicine, Bologna, Italy; European Institute of Oncology, IEO, Milan, Spain.
Abstract
BACKGROUND: Early-interim fluorodeoxyglucose (FDG)-PET scan after two ABVD (doxorubicin, bleomycin, vinblastine, and dacarbazine) chemotherapy courses (PET-2) represents the most effective predictor of treatment outcome in classical Hodgkin's lymphoma. We aimed to assess the predictive value of PET-2 combined with tissue biomarkers in neoplastic and microenvironmental cells for this disease. METHODS: We enrolled 208 patients with classical Hodgkin's lymphoma and treated with ABVD (training set), from Jan 1, 2002, to Dec 31, 2009, and validated the results in a fully matched independent cohort of 102 patients with classical Hodgkin's lymphoma (validation set), enrolled from Jan 1, 2008, to Dec 31, 2012. The inclusion criteria for both the training and validation sets were: the availability of a representative formalin-fixed, paraffin-embedded tissue sample collected at diagnosis; treatment with ABVD with or without radiotherapy; baseline staging and interim restaging after two ABVD courses with FDG-PET; no treatment change based solely on interim PET result; and HIV-negative status. We used Cox multivariate analysis classification and regression tree (CART) to compare the predictive values of these markers with that of PET-2 and to assess the biomarkers' ability to correctly classify patients whose outcome was incorrectly predicted by PET-2. FINDINGS: In multivariate analysis, PET-2 was the only factor able to predict both progression-free survival (hazard ratio [HR] 33·3 [95% CI 13·6-83·3]; p<0·0001) and overall survival (HR 31·3 [95% CI 3·7-58·9]; p=0·002). In the training set, no factor had a stronger adverse predictive value than a positive PET-2 scan and none was able to correctly reclassify PET-2 positive patients. In PET-2 negative patients, expression of CD68 (≥25%) and PD1 (diffuse or rosetting pattern) in microenvironmental cells, and STAT1 negativity in Hodgkin Reed Sternberg cells identified a subset of PET-2 negative patients with a 3 year progression-free survival significantly lower than that of the remaining PET-2 negative population (21 [64%] of 33 [95% CI 45·2-79·0] vs 130 [95%] of 137 [95% CI 89·4-97·7]; p<0·0001). These findings were reproduced in the validation set. INTERPRETATION: The CART algorithm correctly predicted the response to treatment in more than a half of patients who had a relapse or disease progression despite a negative PET-2 scan, thus increasing the negative predictive value of PET-2. In keeping with preliminary results from interim PET response adapted clinical trials of patients with advanced Hodgkin's lymphoma, there might be a non-negligible proportion of treatment failures in the interim PET negative group treated with standard ABVD. FUNDING: Italian Association for Cancer Research, Bologna Association against leukaemia, lymphoma and myeloma, and Bologna University.
BACKGROUND: Early-interim fluorodeoxyglucose (FDG)-PET scan after two ABVD (doxorubicin, bleomycin, vinblastine, and dacarbazine) chemotherapy courses (PET-2) represents the most effective predictor of treatment outcome in classical Hodgkin's lymphoma. We aimed to assess the predictive value of PET-2 combined with tissue biomarkers in neoplastic and microenvironmental cells for this disease. METHODS: We enrolled 208 patients with classical Hodgkin's lymphoma and treated with ABVD (training set), from Jan 1, 2002, to Dec 31, 2009, and validated the results in a fully matched independent cohort of 102 patients with classical Hodgkin's lymphoma (validation set), enrolled from Jan 1, 2008, to Dec 31, 2012. The inclusion criteria for both the training and validation sets were: the availability of a representative formalin-fixed, paraffin-embedded tissue sample collected at diagnosis; treatment with ABVD with or without radiotherapy; baseline staging and interim restaging after two ABVD courses with FDG-PET; no treatment change based solely on interim PET result; and HIV-negative status. We used Cox multivariate analysis classification and regression tree (CART) to compare the predictive values of these markers with that of PET-2 and to assess the biomarkers' ability to correctly classify patients whose outcome was incorrectly predicted by PET-2. FINDINGS: In multivariate analysis, PET-2 was the only factor able to predict both progression-free survival (hazard ratio [HR] 33·3 [95% CI 13·6-83·3]; p<0·0001) and overall survival (HR 31·3 [95% CI 3·7-58·9]; p=0·002). In the training set, no factor had a stronger adverse predictive value than a positive PET-2 scan and none was able to correctly reclassify PET-2 positive patients. In PET-2 negative patients, expression of CD68 (≥25%) and PD1 (diffuse or rosetting pattern) in microenvironmental cells, and STAT1 negativity in Hodgkin Reed Sternberg cells identified a subset of PET-2 negative patients with a 3 year progression-free survival significantly lower than that of the remaining PET-2 negative population (21 [64%] of 33 [95% CI 45·2-79·0] vs 130 [95%] of 137 [95% CI 89·4-97·7]; p<0·0001). These findings were reproduced in the validation set. INTERPRETATION: The CART algorithm correctly predicted the response to treatment in more than a half of patients who had a relapse or disease progression despite a negative PET-2 scan, thus increasing the negative predictive value of PET-2. In keeping with preliminary results from interim PET response adapted clinical trials of patients with advanced Hodgkin's lymphoma, there might be a non-negligible proportion of treatment failures in the interim PET negative group treated with standard ABVD. FUNDING: Italian Association for Cancer Research, Bologna Association against leukaemia, lymphoma and myeloma, and Bologna University.
Authors: Peter Hollander; Peter Kamper; Karin Ekstrom Smedby; Gunilla Enblad; Maja Ludvigsen; Julie Mortensen; Rose-Marie Amini; Stephen Hamilton-Dutoit; Francesco d'Amore; Daniel Molin; Ingrid Glimelius Journal: Blood Adv Date: 2017-08-08